Search (181 results, page 9 of 10)

  • × theme_ss:"Retrievalstudien"
  1. Cleverdon, C.W.; Mills, J.: ¬The testing of index language devices (1985) 0.00 
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  2. Lioma, C.; Ounis, I.: ¬A syntactically-based query reformulation technique for information retrieval (2008) 0.00 
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    Abstract
    Whereas in language words of high frequency are generally associated with low content [Bookstein, A., & Swanson, D. (1974). Probabilistic models for automatic indexing. Journal of the American Society of Information Science, 25(5), 312-318; Damerau, F. J. (1965). An experiment in automatic indexing. American Documentation, 16, 283-289; Harter, S. P. (1974). A probabilistic approach to automatic keyword indexing. PhD thesis, University of Chicago; Sparck-Jones, K. (1972). A statistical interpretation of term specificity and its application in retrieval. Journal of Documentation, 28, 11-21; Yu, C., & Salton, G. (1976). Precision weighting - an effective automatic indexing method. Journal of the Association for Computer Machinery (ACM), 23(1), 76-88], shallow syntactic fragments of high frequency generally correspond to lexical fragments of high content [Lioma, C., & Ounis, I. (2006). Examining the content load of part of speech blocks for information retrieval. In Proceedings of the international committee on computational linguistics and the association for computational linguistics (COLING/ACL 2006), Sydney, Australia]. We implement this finding to Information Retrieval, as follows. We present a novel automatic query reformulation technique, which is based on shallow syntactic evidence induced from various language samples, and used to enhance the performance of an Information Retrieval system. Firstly, we draw shallow syntactic evidence from language samples of varying size, and compare the effect of language sample size upon retrieval performance, when using our syntactically-based query reformulation (SQR) technique. Secondly, we compare SQR to a state-of-the-art probabilistic pseudo-relevance feedback technique. Additionally, we combine both techniques and evaluate their compatibility. We evaluate our proposed technique across two standard Text REtrieval Conference (TREC) English test collections, and three statistically different weighting models. Experimental results suggest that SQR markedly enhances retrieval performance, and is at least comparable to pseudo-relevance feedback. Notably, the combination of SQR and pseudo-relevance feedback further enhances retrieval performance considerably. These collective experimental results confirm the tenet that high frequency shallow syntactic fragments correspond to content-bearing lexical fragments.
  3. Voorhees, E.M.; Harman, D.K.: ¬The Text REtrieval Conference (2005) 0.00 
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    Source
    TREC: experiment and evaluation in information retrieval. Ed.: E.M. Voorhees, u. D.K. Harman
  4. Iivonen, M.: Consistency in the selection of search concepts and search terms (1995) 0.00 
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    Abstract
    Considers intersearcher and intrasearcher consistency in the selection of search terms. Based on an empirical study where 22 searchers from 4 different types of search environments analyzed altogether 12 search requests of 4 different types in 2 separate test situations between which 2 months elapsed. Statistically very significant differences in consistency were found according to the types of search environments and search requests. Consistency was also considered according to the extent of the scope of search concept. At level I search terms were compared character by character. At level II different search terms were accepted as the same search concept with a rather simple evaluation of linguistic expressions. At level III, in addition to level II, the hierarchical approach of the search request was also controlled. At level IV different search terms were accepted as the same search concept with a broad interpretation of the search concept. Both intersearcher and intrasearcher consistency grew most immediately after a rather simple evaluation of linguistic impressions
  5. Wood, F.; Ford, N.; Miller, D.; Sobczyk, G.; Duffin, R.: Information skills, searching behaviour and cognitive styles for student-centred learning : a computer-assisted learning approach (1996) 0.00 
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    Source
    Journal of information science. 22(1996) no.2, S.79-92
  6. Crestani, F.; Rijsbergen, C.J. van: Information retrieval by imaging (1996) 0.00 
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    Source
    Information retrieval: new systems and current research. Proceedings of the 16th Research Colloquium of the British Computer Society Information Retrieval Specialist Group, Drymen, Scotland, 22-23 Mar 94. Ed.: R. Leon
  7. Leininger, K.: Interindexer consistency in PsychINFO (2000) 0.00 
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    Date
    9. 2.1997 18:44:22
  8. Mettrop, W.; Nieuwenhuysen, P.: Internet search engines : fluctuations in document accessibility (2001) 0.00 
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  9. Radev, D.R.; Libner, K.; Fan, W.: Getting answers to natural language questions on the Web (2002) 0.00 
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  10. Saracevic, T.: Effects of inconsistent relevance judgments on information retrieval test results : a historical perspective (2008) 0.00 
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    Content
    Beitrag in einem Themenheft 'The Influence of F. W. Lancaster on Information Science and on Libraries', das als Festschrift für F.W. Lancaster deklariert ist.
  11. Belkin, N.J.: ¬An overview of results from Rutgers' investigations of interactive information retrieval (1998) 0.00 
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    Date
    22. 9.1997 19:16:05
  12. King, D.W.: Blazing new trails : in celebration of an audacious career (2000) 0.00 
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    Date
    22. 9.1997 19:16:05
  13. Petrelli, D.: On the role of user-centred evaluation in the advancement of interactive information retrieval (2008) 0.00 
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    Source
    Information processing and management. 44(2008) no.1, S.22-38
  14. Chu, H.: Factors affecting relevance judgment : a report from TREC Legal track (2011) 0.00 
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    Date
    12. 7.2011 18:29:22
  15. Wildemuth, B.; Freund, L.; Toms, E.G.: Untangling search task complexity and difficulty in the context of interactive information retrieval studies (2014) 0.00 
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    Date
    6. 4.2015 19:31:22
  16. Ravana, S.D.; Taheri, M.S.; Rajagopal, P.: Document-based approach to improve the accuracy of pairwise comparison in evaluating information retrieval systems (2015) 0.00 
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    Date
    20. 1.2015 18:30:22
  17. Rajagopal, P.; Ravana, S.D.; Koh, Y.S.; Balakrishnan, V.: Evaluating the effectiveness of information retrieval systems using effort-based relevance judgment (2019) 0.00 
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    Date
    20. 1.2015 18:30:22
  18. Lancaster, F.W.: Evaluating the performance of a large computerized information system (1985) 0.00 
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    Abstract
    F. W. Lancaster is known for his writing an the state of the art in librarylinformation science. His skill in identifying significant contributions and synthesizing literature in fields as diverse as online systems, vocabulary control, measurement and evaluation, and the paperless society have earned him esteem as a chronicler of information science. Equally deserving of repute is his own contribution to research in the discipline-his evaluation of the MEDLARS operating system. The MEDLARS study is notable for several reasons. It was the first large-scale application of retrieval experiment methodology to the evaluation of an actual operating system. As such, problems had to be faced that do not arise in laboratory-like conditions. One example is the problem of recall: how to determine, for a very large and dynamic database, the number of documents relevant to a given search request. By solving this problem and others attendant upon transferring an experimental methodology to the real world, Lancaster created a constructive procedure that could be used to improve the design and functioning of retrieval systems. The MEDLARS study is notable also for its contribution to our understanding of what constitutes a good index language and good indexing. The ideal retrieval system would be one that retrieves all and only relevant documents. The failures that occur in real operating systems, when a relevant document is not retrieved (a recall failure) or an irrelevant document is retrieved (a precision failure), can be analysed to assess the impact of various factors an the performance of the system. This is exactly what Lancaster did. He found both the MEDLARS indexing and the McSH index language to be significant factors affecting retrieval performance. The indexing, primarily because it was insufficiently exhaustive, explained a large number of recall failures. The index language, largely because of its insufficient specificity, accounted for a large number of precision failures. The purpose of identifying factors responsible for a system's failures is ultimately to improve the system. Unlike many user studies, the MEDLARS evaluation yielded recommendations that were eventually implemented.* Indexing exhaustivity was increased and the McSH index language was enriched with more specific terms and a larger entry vocabulary.
  19. Dzeyk, W.: Effektiv und nutzerfreundlich : Einsatz von semantischen Technologien und Usability-Methoden zur Verbesserung der medizinischen Literatursuche (2010) 0.00 
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  20. Larsen, B.; Ingwersen, P.; Lund, B.: Data fusion according to the principle of polyrepresentation (2009) 0.00 
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    Date
    22. 3.2009 18:48:28

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